The Novel Gamma Secretase Inhibitor RO4929097 Reduces the Tumor Initiating Potential of Melanoma
Bibliographic record
Abstract
Several reports have demonstrated a role for aberrant NOTCH signaling in melanoma genesis and progression, prompting us to explore if targeting this pathway is a valid therapeutic approach against melanoma. We targeted NOTCH signaling using RO4929097, a novel inhibitor of gamma secretase, which is a key component of the enzymatic complex that cleaves and activates NOTCH. The effects of RO4929097 on the oncogenic and stem cell properties of a panel of melanoma cell lines were tested both in vitro and in vivo, using xenograft models. In human primary melanoma cell lines, RO4929097 decreased the levels of NOTCH transcriptional target HES1. This was accompanied by reduced proliferation and impaired ability to form colonies in soft agar and to organize in tridimensional spheres. Moreover, RO4929097 affected the growth of human primary melanoma xenograft in NOD/SCID/IL2gammaR-/- mice and inhibited subsequent tumor formation in a serial xenotransplantation model, suggesting that inhibition of NOTCH signaling suppresses the tumor initiating potential of melanoma cells. In addition, RO4929097 decreased tumor volume and blocked the invasive growth pattern of metastatic melanoma cell lines in vivo. Finally, increased gene expression of NOTCH signaling components correlated with shorter post recurrence survival in metastatic melanoma cases. Our data support NOTCH inhibition as a promising therapeutic strategy against melanoma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".